Computational Physics

Since the fundamental equations of physics can in general not be solved analytically, computer simulations play a very important role in science. Simulations can be done on the atomic scale where the Schroedinger equation together with the laws of statistical physics allow in principle to describe all phenomena in solid state physics, chemistry and materials sciences. Simulations can however also be done on much larger scales to simulate for instance supernovae. Due to the rapidly increasing speed of computers, simulation is a very active field with many opportunities to improve simulation methods and with new applications becoming feasible.

Simulation methods are a powerful tool to determine the structure and electronic properties of condensed matter systems. We develop better algorithms for such atomistic calculations and apply them to challenging problems. The research has interdisciplinary character, involving physics, mathematics, chemistry and computer science. The main application is in the area of materials sciences, where we predict by simulations new materials with interesting properties mainly in the field of renewable energy production and storage. Finding ground state structures requires finding the global minimum of the potential energy surface. This can be done with the minima hopping algorithm (Goedecker, J. Chem. Phys 120, 9911 (2004)). The visualization of the minima hopping algorithm shows the formation of a fullerene molecule out of a graphite sheet containing 60 carbon atoms. Even though silicon is one of the best studied material, many interesting structures went undetected until very recently (Maximilian Amsler, et al., Physical Review B 92, 014101 (2015)). The picture shows some novel low density silicon structures with interesting properties for photo-voltaic applications.

Macroscopic phenomena in nature - in astrophysics and on Earth - often originate from the interaction of tightly coupled microscopic processes with different characteristic length and time scales. We develop efficient transport/hydrodynamics algorithms in the context of gravitational collapse and supernova explosions. A reliable numerical link between the input physics and the observables in distant astrophysical objects provides new information about matter under otherwise inaccessible conditions, or vice versa, allows the prediction of a large-scale evolution based on well-known input physics.